While surveillance cameras have been utilized in a variety of applications for many years, the ability to analyze video data via video analytics systems has dramatically increased the capability of the surveillance camera. For example, video analytic systems may be utilized to automatically detect and track users within the field of view of the surveillance camera. This type of video analytic system may be particularly useful in applications in which it is desired to get a “count” of the number of users passing through a particular region. However, the accuracy of such systems depends not only on the particulars of the video analytic system but also on the environment in which the system is installed. A system that works well in one environment may struggle to operate as well in another environment. For example, a video analytic system that relies on visible light video data may work well during the day, but may struggle to identify users or people during low-light or night conditions.
There is therefore a need to continue to improve the capability of video analytic systems to operate accurately in a variety of applications/conditions.